ICT self-efficacy items

The ICT self-efficacy measure comprised two scales that assessed the individuals’ self-efficacy in relation to ICT. According to Kay (1993), attitudes to computers are determined by four aspects, the individuals’ behaviour (actual skill), cognitive (belief), perceived control and affect (anxiety). Following Kay (1993) four measures were originally developed measuring these four constructs, namely ICT skill, attitude, perceived control and anxiety. However after the Exploratory Factor Analysis (EFA) only two constructs were retained; as ICT attitude strongly cross loaded with perceived control both these measures were removed (see section 3.7 of this chapter for more details regarding the EFA). Figure 9 briefly outlines the remaining two constructs. These two constructs (ICT skill and anxiety) will be discussed in the next two sections of this chapter.

Figure 9: The two constructs that comprise ICT self-efficacy.

3.5.1.1 ICT Skill.

The general ICT skill scale was made up of several technology tasks. Participants were asked to rate their skill on each task. The tasks used in this study were taken from Kennedy, Dalgarno, Bennett, Judd, Gray and Chang (2008). The study conducted by Kennedy et al. (2008) included determining the most commonly used technology-based activities of student and staff. The original survey contained 38 tasks that were grouped into eight categories. The pilot test (see section 3.6) was used to reduce this number to 16 key activities that related to both computer and mobile usage. Computer based activities required a range of skills from using word

processing software to searching and downloading files from the Internet. Mobile device usage included items relating to activities such as sending and receiving texts to uploading programs onto their phone. The skill was assessed based on a 7-point scale: 1= “Never used” to 7=” Extremely skilled”. Based on EFA (see section 3.7) these 16 tasks were grouped into three key groups, namely tasks associated with everyday ICT usage (referred to as general ICT skill), tasks associated with expert or specialised ICT usage (referred to advanced ICT skill) and tasks associated with mobile usage (referred to specific mobile skill). General ICT skill assessed the competency of users in relation to general computing tasks, such as using word processing software, searching and emailing on the Internet and doing basic mobile activities, such as texting and calling. Advanced ICT skill assessed the competency of users in relation to more advanced computing, such as modifying images and sounds and using advanced software (such as Skype). Specific mobile skill related to using mobile technology for more complex mobile learning activities, such as accessing the Internet, emailing and sending photos. In each category

four items were retained to represent each construct (r = .80 for students, r = .84 for educators).

The motivation for determining participants’ skill using a range of technologies came from the assertion that students and educators skilled in wide range of technologies were more likely to adopt new technology (Hackbarth, et al., 2003). In their study they found that as people become

Perceived

Anxiety

Measures the level of anxiousness the individual feels when using ICT – an individual that is highly anxious about having to use ICT will be less likely not to adopt ICT.

ICT self-efficacy

ICT skill

Self rated ability/skill of individuals related to their skill to use a range of tasks focused on basic to expert computing and mobile use.

more experienced with ICT tools, and learnt the necessary skills to use them, they were more likely to develop a favourable perception of the tool and feel at ease when using the tool. In addition, as discussed in Theng (2009), people tend to adopt information systems that are compatible to those previously adopted and used. In reference to mobile use, Theng (2009) found that student perceptions of ease of use about mobile devices as learning tool was significantly related to the students’ prior experience of using mobile devices. This study attempted to determine the impact of a user’s self-reported ICT skill and attitude on their intention to adopt mobile learning. In particular the following hypotheses were tested:

• H1-3 a and b: Students/educators with higher levels of general ICT skill (H1), advanced

ICT skill (H2) and/or specific mobile skill (H3) will more likely to see mobile learning as easy to use and useful.

• H4-6: Students/educators with higher levels of general ICT skill (H4), advanced ICT skill

(H5), and/or specific mobile skill (H6) will be more likely to adopt mobile learning.

In addition, the following relationships were tested.

• H7-9: As users become more skilled in one area of ICT usage they will be more likely to

adopt a wider use of a range of ICT technologies.

Figure 10 illustrates these hypotheses.

Figure 10: The hypothesis related to ICT skill.

General ICT Skill Specific Mobile Skill Advanced ICT Skill Perceived Ease of Use Perceived Usefulness Behavioural Intention IC T S k il l Tec h n o lo g y A cc e p ta n ce M o d el H1a H1b H2a H2b H3a H3a H4 H5 H6 H7 H8 H9

3.5.1.2 ICT anxiety.

In addition, to the self-assessed skill used to measure ICT self-efficacy, eleven additional

statements were used to assess the individual’s attitude towards the use of ICT. The statements related to three general areas, general attitude to ICT, perceived control over ICT and anxiety. However, high levels of cross-loading in the EFA resulted in the retention of only anxiety for further analysis.

The anxiety measure was adapted from Wilfong (2006) and measured the level of anxiety felt when confronted with the issue of having to use ICT. Research has shown that an individual who is highly anxious about having to use ICT will be less likely to use ICT in their learning (Barbeite & Weiss, 2004; Beckers & Schmidt, 2003; Wilfong, 2006). This scale was measured using

statements such as, “I feel apprehensive when using a computer” and “I have a lot of confidence when it comes to working with information and communication technology”. These statements were all measured using a 7-point likert-type scale: 1 =“strongly disagree” to 7 = “strongly

agree.” Four items were retained to represent the ICT anxiety construct (r = .80 for students, r =

.70 for educators).

ICT anxiety was used to determine the impact of anxiety on the intention to adopt, and attitude to, mobile learning. In particular two hypotheses were tested:

• H 10 a and b: Students/educators with lower ICT anxiety will be more likely to see

mobile learning as easy to use and useful.

• H11: Students/educators with lower ICT anxiety will be more likely to adopt mobile

learning.

In addition, the following relationships were tested.

• H12-14: As a user becomes more competent with one or more of the ICT skill areas they

will experience less anxiety.

Figure 11: The hypothesis that relate to ICT anxiety.